Platform Strategy – by Sangeet Paul Choudaryhttp://platformed.info
Tue, 06 Dec 2016 06:13:14 +0000en-UShourly1https://wordpress.org/?v=4.6.1Connected but unequal: The mechanics of inequality in a networked worldhttp://feedproxy.google.com/~r/platformed/~3/gCREOOXBo5g/
http://platformed.info/connected-but-unequal-the-mechanics-of-inequality-in-a-networked-world/#respondTue, 06 Dec 2016 05:59:44 +0000http://platformed.info/?p=6870If we closely analyze the mechanics that drive todays platforms and networks, we learn — rather disturbingly — that digital platforms are designed to drive greater social inequality, not reduce it.

This is ironic because we’ve often thought of networks as infrastructures for fairer distribution. We understand that robots are bad, they’re out to eat all jobs, and our dystopian fears are closer than we think. We get that!

But networks and platforms? They often seem to form the silver lining in the technology-breeds-inequality debate. If platforms re-intermediate market interactions more efficiently — the argument goes — then they should be making the world more equal by democratizing resource access for everyone. Or so the gig economy enthusiasts would have us believe.

Why wouldn’t an algorithm-driven world of platforms make things more equal? Why would it, instead, drive further inequality?

This isn’t meant to be a comprehensive treatise on inequality. Sharing economy enthusiasts often claim that while some of technology may be driving inequality, platforms — and, in particular, labor platforms — will create more access and choice and help reduce inequality. This article focuses only on understanding whether greater democratization and lower inequality is inherent to a more networked world.

Let’s look at the mechanics of platforms to understand this better. The impact of platforms may be analysed at two distinct layers:

1. The layer of the ecosystem that builds around the platform

2. The layer of the firm that powers the platform

Let’s dive into the mechanics of the ecosystem first.

THE ECOSYSTEM

Ecosystems around platforms scale non-linearly and in the course of such non-linear adoption, platforms need to scale their curation and quality control to manage ecosystem interactions. Most platforms do this by instituting reputation systems.

Mechanic #1: Reputation systems

Reputation systems track, determine, and encode the reputation of different participants in the ecosystem. These participants are consequently accorded market access and influence based on how reputed they are. As an example, Airbnb hosts who get booked and rated higher more often are likely to show up higher on search results. Higher reputation leads to greater market access and influence.

From the perspective of the ecosystem members, the rules of market access change. Instead of appealing to an unscalable, editorial gatekeeper, you pander to an algorithm, driven by social feedback. Instead of auditioning to a judging panel, you go viral on YouTube. In most cases, a market-driven system to determine access is fairer than one based solely on human judgment. However, it’s not necessarily making the ecosystem more equal.

It’s merely changing the rules on which the inequality operates.

One may argue that inequality is a feature, not a bug, of any meritocratic system. There is, therefore, nothing wrong with a new inequality.

That sounds fine, until you combine Mechanic #1 with the other four mechanics that drive further inequality on platforms.

Mechanic #2: Positive feedback loops

We noted above that higher reputation leads to higher market access and influence.

In a connected ecosystem, higher market access and influence, lead to more interactions for users, which — potentially — further increases their reputation. A virtuous cycle sets in.

Reputation systems benefit from these positive feedback loops. The higher your reputation, the greater your influence, the greater the likelihood that you attract further ratings. The ones who have it tend to get even more while the others find it difficult to solve the cold start problem.

On platform-mediated markets, the rich get richer and the poor get stuck.

The notion of feedback loops is an important one not just at the level of individual platforms but at the level of the overall internet as well. People who build reputation and influence across multiple platforms, rapidly realize that the cross-feedback between different platforms, once connected well enough, brings in further non-linear increase. Feedback loops operate in any connected system and as various aspects of our economy get more connected, their ability to drive further inequality increases in ways that cannot always be traced.

Positive feedback loops, when implemented unchecked in a system, drive greater concentration of value at the top, hollow out the middle, and drive the majority of the participants further down. As a result, those who rise to the top benefit from feedback and emerge as superstars while those who stay at the bottom find it increasingly difficult to break through. Positive feedback loops are the primary driver for greater inequality in a connected system.

System designers often solve this problem by damping the impact of positive feedback loops. To counter unchecked positive feedback, well structured systems architect negative feedback into the system. We will note, however, over the course of exploring the next two mechanics, that platforms are naturally incentivised to inhibit negative feedback and promote more positive feedback.

But, you’d argue, we’re structuring positive feedback based on market reputation for the overall good — improving the quality of interactions on the platform. We’re simply allowing the market to choose who gets more and the market will reward quality.

The logic works well, except for one important caveat.

Mechanic #3: Unfair advantage

Platforms often deliberately encourage unfairness. This doesn’t stem from malice. All unfairness, as we’ll note shortly, is in the best interest of good platform execution.

To start with, an unfair advantage is baked into the very workings of a platform. Since there’s a feedback loop in play, the users who come in earlier and invest in the platform gain a significant first mover advantage. They benefit from the feedback loop for a longer period of time. Moreover, the platform also errs on the side of exerting less control on the ecosystem.

Users who come on to the platform much later do not get this early headstart. More importantly, by that time, the wild west days of the platform are over and the platform starts exerting tighter control. Users who created Pages on Facebook in the early days saw greater amplification for their posts and were able to bring in a larger fan base than those who created Pages much later when the platform started clamping down on the amplification of posts.

Hence, users who come on early onto a platform often benefit from an advantage over users who show up late. As time passes on, the ability of every subsequent cohort of users to gather influence on the platform changes significantly.

There is a second form of unfair advantage that some users benefit from, which is deliberately infused by the platform owner. In its early days, a platform often struggles with the cold start problem: users who join the platform rapidly get deactivated because they don’t find great content on the platform.

To solve this problem, platforms often curate a small number of high quality producers in their early days and encourage new users to follow these producers. Early users who get selected during this curation find their influence rapidly amplified by the platform. Users who didn’t join early enough do not benefit from this mechanic despite similar quality.

As the platform grows, it constantly expands the list of suggested users. However, the amplification that the first few high quality users received from the platform, when it was desperate to increase new user activation, is much higher than that received by users who are added to this list later, when the platform achieved steady state and new users joining in have a wide range of high quality content to choose from.

Sometimes, employees of the platform company who participate in the ecosystem may also benefit from this unfair advantage. Adam Rifkin speculates in this Quora answer that Tristan Walker possibly gained a huge following on Twitter because he was an intern at the company when the platform first created a small curated group of users who would be suggested to new users when they joined Twitter. Tristan is excellent at engaging his followers on Twitter but it’s unlikely he would have gained followership at a similar scale if he hadn’t got the headstart that the Suggested Users list provided.

When platforms favor certain users above others, users with similar quality contributions but favoured differently by the platform may end up with very different levels of influence on the platform. Quality alone doesn’t determine influence, as it would in a well-functioning meritocratic market.

There is a significant first mover advantage for users on a growing platform.

A rising tide lifts some boats much higher than the rest. And then, the feedback loop kicks in. Users who get a headstart because they were favoured by the platform during the early days benefit from increasingly higher amplification in the days ahead. The gulf between the haves and have-nots increases further, not entirely based on merit, but based on being at the right place at the right time.

There is a fourth mechanic at play which makes the effect of feedback loops much stronger.

Mechanic #4: Global reputation trumps local reputation

Before the invention of recorded media, artists thrived on local reputation. Every town would reward its local artists. Theater flourished and local singers made a good living entertaining their local audiences. Artists flourished not on the basis of the quality of their art but on the strength of their locally accessible audience. A few would break through this barrier, build larger reputation, and travel to many different patrons and audiences.

The invention of recorded media changed everything. Audiences didn’t care about listening to live local artists when they could listen to the best voices over recorded media. The discovery of the best artists led to further patronization by wealthy families, which led to the rise of a few superstars and the decline of all others. Audience adoption and patronization by the wealthy concentrated among a few artists, changing the mechanics of the industry and giving rise to superstars.

Something similar played out with the death of theater and the rise of Hollywood. As the quality of movie recordings improved, theater actors struggled to compete. Over time, theater started working more on global reputation as well with a few (Broadway, West End) concentrating the best talent and with actor touring the world to harvest their global reputation.

The technology of recorded media drove inequality in the creative industries. Global reputation trumped local reputation. Today, we take this inequality for granted in the creative industries. But we’re now seeing other professions giving rise to similar superstar economics.

In the age of networks, any form of work that rewards global reputation over local reputation will see increasing inequality.

Job/task marketplaces rely heavily on reputation systems to match the best service providers with customers. The more specialized the job, the greater the importance of the reputation system. In the case of information-oriented jobs, that do not require physical co-location, global reputation starts trumping local reputation. High-end consulting, data science etc. are already seeing this set in with high-skills marketplaces polarizing and amplifying the earning potential of a few highly reputed workers who serve clients globally. Consumers on these platforms prefer hiring the best talent, irrespective of geography. Prior to the existence of these platforms, and online professional networks like LinkedIn, consumers would prioritise convenience in search over quality. Local reputation mattered more than global reputation, much like it did for singers before recorded media was invented.

As more skilled work moves on to platforms, many more markets will start demonstrating the superstar economics that we already see in the creative industries. Whenever global reputation matters more than local reputation and a platform re-intermediates such a market effectively, the few top workers will command inordinately high prices.

Again, workers who show up early on such a platform have a better shot at mechanics #1, #2, and #3 working for them.

There is one final mechanic that determines which markets will allow greater social mobility.

Mechanic #5: Specialization of skills

Let’s move the discussion from highly specialized labor to low skilled work. Unlike specialized work, low skill work isn’t just low pay, it also comes with relatively low career progression.

We understand this intuitively. High skill work attracts significant career progression, low skill work involves low progression as well.

In a networked world, this gets worse.

In a feature report in the MIT Technology Review last year, I noted that platforms that orchestrate specialized labor tend to play fairer to their ecosystem than those that orchestrate unskilled labor. Rentacoder vs. Uber is a case in point. Rentacoder supply is highly specialized and differentiated. Customers are highly sensitive to quality. Uber supply, in contrast, is very commodified. All rides are roughly the same, above a minimum threshold of quality. Decision making on Uber boils down to finding the nearest available vehicle at that particular time. Customer decision making on Rentacoder is much more nuanced. Customers consider multiple factors while making a decision and the order of importance of these factors varies from one customer to the next.

This, of course, is the nature of markets. Commodities eventually compete on price and convenience. However, this shows why the gig economy is not the panacea for rising unemployment that it is made out to be. Skilled but unemployed people who enter the gig economy for commodified work (think TaskRabbit, Zaarly etc.) will have a harder time making their way back to any form of skilled work. Undifferentiated gig workers work in markets which do not allow any meaningful form of career progression. In skilled labor markets, the reputation systems of platforms help the best workers rise to the top. Unskilled labor markets leverage reputation systems only to weed out the bottom, not necessarily to amplify outcomes for the top (Think Uber removing drivers at the bottom but not increasing rewards for top-performing drivers).

In an age of platforms, the gap between skilled labor and unskilled labor will get further amplified.

—

As the five mechanics above demonstrate, networked systems are naturally architected to drive greater inequality.

At this point, let’s shift gears and move away from the ecosystem to the firm. In a connected world, there will be a divide within the ecosystem. But there will be a greater divide between the firm and the ecosystem.

THE FIRM

This part of the argument is more along the lines of throwing rocks at the Google Bus. However, understanding the mechanics at play is helpful.

We are quick to sloganize that programmers are ruling the world and everyone should start programming. Not only is that the wrong conclusion to jump to (all sweeping sloganize that programmers are ruling the world and everyone should start programming. Not only is that the wrong conclusion to jump to (all sweeping generalisations of this type are), it also successfully glosses over the mechanics at play.

Programming has been around for a long time. However, the rates at which value has been captured by programmers has been captured by programmers has changed over the last decade. Over the last decade, and a little before that, we’ve realized that a networked world offers a unique opportunity to leverage labor and property outside the firm to create profits for the firm.

The math works out great. Platform businesses like Facebook, Google, Uber, and UpWork grow their ecosystem at near-zero marginal costs of expansion but benefit from the property and labor that is owned by the ecosystem. The costs of managing the property and labor are passed on to the ecosystem while a portion of the profits UpWork grow their ecosystem at near-zero marginal costs of expansion but benefit from the property and labor that is owned by the ecosystem. The costs of managing the property and labor are passed on to the ecosystem while a portion of the profits accrue to the platform.

This is where programming comes in.

Programmers that improve the platform’s ability to scalably orchestrate such interactions in the ecosystem are highly valued because they are able to scale value capture back to the platform non-linearly.

All programming may not pay well but any programming (and associated skills) that enable a large platform to capture greater value, through better orchestration of the ecosystem, is going to be highly valued.

This, in turn, drives significant inequality between those who are employed by such firms and those who work it out in the ecosystem.

—

Solving inequality through architecture

The architecture of networks and platforms isn’t really helping reduce inequality, it is instead poised to drive it further. Across the mechanics laid out above, we note how markets that reward meritocracy drive further inequality in an age of platforms. Moreover, not all of this inequality is merit-based, some of it can be attributed to a more structural form of luck as evidenced by Mechanic #3.

We did propose an architectural solution to a more equal world in the narrative above: the deliberate design of negative feedback loops to dampen the system. However, as mechanics #3 and #4 demonstrate, platforms shy away from deliberate damping when (i) it comes in the way of user activation on the platform (Mechanic #3), and (ii) global reputation trumps local reputation, as is the case with a lot of specialized, knowledge work (Mechanic #4).

Connectivity is going to be great for the world. Connectivity will drive access to a better life. But if we expect connectivity to solve the problem of inequality, we will need to deliberately address this issue in the architecture of the connected systems that we build. Inequality rises from architecture, and to some extent, can be resolved within the architecture.

We’ve seen repeatedly in the evolution of social systems that policy, alone, is ineffective at solving inequality. Policy needs to be complemented by architecture.

But in order to do that, we need to make deliberate choices in the architecture of the ecosystems, optimizing not merely for ecosystem performance but for democratic progression and equal access to the opportunities a networked world offers. As we noted above, positive feedback loops of reputation and quality are allowed to work in many platform architectures because they help create a stronger ecosystem. However, working unfettered, these cycles can reduce access to opportunities and progression for users, unless dampened deliberately. This dampening doesn’t have to come at a cost to platform performance, but it does need to be accompanied by a rearchitecture that balances the need for maximizing ecosystem output with the need for balancing access and progression within the ecosystem.

Architecture helps us understand the systems we inhabit. Hopefully, architecture can help us manage some of their complexities better as we move forward.

]]>http://platformed.info/connected-but-unequal-the-mechanics-of-inequality-in-a-networked-world/feed/0http://platformed.info/connected-but-unequal-the-mechanics-of-inequality-in-a-networked-world/What casinos and crime teach us about new tech use caseshttp://feedproxy.google.com/~r/platformed/~3/aQZWRYgzrZU/
http://platformed.info/what-casinos-and-crime-teach-us-about-new-tech-use-cases/#respondMon, 24 Oct 2016 06:48:26 +0000http://platformed.info/?p=6689One of the best ways to understand the future is to study industries that have artificials constraints and work their way on figuring out a way around these constraints. These industries often tend to be most innovative and define new technology use cases way before those use cases get mainstream adoption. There are four industries that regularly demonstrate these characteristics:
1) Terrorism and related crime
2) Adult entertainment
3) Drug trafficking
4) Gambling

I am, of course, using the term ‘industry’ loosely here. These industries have always stayed a few steps ahead of the rest. For example, the primary use case of drug trafficking on Silk Road was one of the first large scale implementations of the blockchain, much more before it fascinated the financial servcies industry. The adult entertainment industry was the first to monetize content effectively on the internet, something that the traditional media still struggles to do. Terrorism used technology to manage remote decentralized teams using mobile networks way before fleet managers and distributed sales teams figured out the mechanics of doing that. We’ve repeatedly seen these industries leverage technology to figure out use cases and discover mechanics way before traditional industries do.

Gambling, in particular is a very interesting industry. Casinos, themselves, have always served as multi-sided interaction environments where the platform (casino) always wins by knowing more about the interactions than any individual participant.

The gambling industry was the first to formalized and implement behaviour design. Casinos have repeatedly worked on creating behavior design schedules so that users keep coming back and participating further. These principles subsequently found their way into other industries like advertising and gaming, and subsequently into social media.

The gambling industry also instituted one of the first large scale implementations of mass personalization, using data. Casinos have always built specific strategies to target whales – gamblers who spend extraordinarily high amounts and are accordingly treated with different incentives. With a wealth of data, casinos have been working on scaling whale-type incentives across a larger base of players, and on automating their experience journey with the casino. Data-driven mass personalization is increasingly entering other industries. Personalised experiences that were once served only to the top 1% are moving onto a larger base. Wealth management is one such industry where a handful of high net worth individuals get highly personalized advice but the middle layer of investors is served with products and services, not necessarily with personalized investment advice. With the advent of robo advisors, we will see technology augment human workers enabling a larger base of advisors to scale their investment advisory with lower skill requirements and on better economics, allowing them to cater to a much larger group of investors.

I believe we will see something similar in the early adoption of VR and automation, and will be keeping an eye out for unexpected use cases in these spaces.

]]>http://platformed.info/what-casinos-and-crime-teach-us-about-new-tech-use-cases/feed/0http://platformed.info/what-casinos-and-crime-teach-us-about-new-tech-use-cases/THE REINTERMEDIATION OF MARKETShttp://feedproxy.google.com/~r/platformed/~3/pU2bfDQ4iws/
http://platformed.info/the-reintermediation-of-markets/#respondWed, 07 Sep 2016 04:42:03 +0000http://platformed.info/?p=6627One of the most widespread narratives around the impact of the internet centers around the belief that the internet disintermediates markets. In the truest sense of the word, the internet never disintermediates. Instead, digital platforms reintermediate markets in much more efficient ways. There are a few common themes that recur when digital platforms come in and reintermediate markets.

BETTER DATA SIGNALS

Platforms rely on better data signals to determine matching of supply and demand. Platforms like Amazon Kindle Publishing behave more efficiently than traditional publishing houses, leveraging algorithms and social feedback to determine exposure of books and authors.

Implications for Pipes:

This has important implications for pipeline companies, many of whom are intermediaries. Banks, for example, need to start employing better data signals to perform their roles as intermediaries. Credit scoring towards lending still follows an archaic data model with limited static set of fields that are used as inputs. Insurance premiums also work on an inefficient data model. In an age where both automobiles and health trackers are getting connected to the internet, insurance firms need to actively rethink their roles as intermediaries or risk having platforms come in with more compelling models

BETTER ECOSYSTEM ECONOMICS

Efficient reintermediation of markets often involves better economics for all parties involved. We’ve seen this play out in the handset and telecom industry where app developers would get 30% or less of sales while selling through traditional telcos. Apple and Google Play flipped the economics, allowing developers to pocket 70% of sales. Platforms scale with far better economics and are often well-placed to transfer economic value back to the ecosystem.

Implications for Pipes:

Intermediaries that have benefited as rent-seekers will start feeling pressure from competitors who will pass on better economics to the ecosystem. In some cases, better economics will be artificially created and subsidized by venture capital. The ecommerce markets in India and Indonesia are seeing this play out at the moment with marketplaces subsidizing both buyers and sellers. These are unlikely to be sustainable in the long run but may still kill a few incumbents while the startups burn venture capital money. However, as Amazon has already demonstrated in the US, and may demonstrate in India as well, new platform intermediaries may benefit from superior fundamentals that allows them to pass on benefits to the ecosystem without having to artificially deflate prices or incentivize suppliers.

BETTER INTERMEDIARY ECONOMICS

Emerging platform intermediaries go beyond better ecosystem economics. They benefit from better intermediary economics as they scale their capabilities by leveraging artificial intelligence to improve their ability to intermediate. Airbnb, for example, can better determine trust models after learning from the behaviors of millions of guests and hosts and predict future behavior in the ecosystem. This improves its ability to intermediate interactions at lower costs of intermediation.

Implications for Pipes:

Traditional intermediaries need to improve the economics of their own intermediation. If much of the intermediation is dependent on human capital and unscalable processes, the intermediary tends to be slow and expensive. Professional services firms will increasingly feel the pressure from more networked enterprises that leverage machine learning and a more fluid networked workforce to compete with a traditional service delivery model. Machine learning will enable services firms, especially those in information-intensive businesses like law and consulting, to scale their capabilities, while a networked workforce will allow these emerging firms to perform with lower fixed costs.

THE OPPORTUNITY FOR PIPES

When platforms disrupted media, telecom, and other information-intensive industries, the efficiency of the new intermediaries and the resulting network effects were so strong that incumbent pipes had very little opportunity to react. We’re seeing a longer disruption cycle with more resource-intensive industries (like B2B supply chains), with more regulated industries (like banking) and with information-intensive services (like law or consulting). Pipe businesses in these industries still have an opportunity to start benefiting from the superior technology (e.g. machine learning) and better ecosystem incentive design that the platforms entering these industries benefit from. This is where pipes may still hold an ounce of advantage and where some of them may end up reinventing themselves successfully as platforms.

]]>http://platformed.info/the-reintermediation-of-markets/feed/0http://platformed.info/the-reintermediation-of-markets/Platform failure: Why the mighty failhttp://feedproxy.google.com/~r/platformed/~3/3NIAGeDEsGY/
http://platformed.info/platform-failure-why-the-mighty-fail/#respondMon, 11 Jul 2016 09:26:52 +0000http://platformed.info/?p=5480This article was originally published on the Harvard Business Review. This article was co-authored with Marshall Van Alstyne and Geoffrey Parker.

The success of platform businesses like Alibaba, Airbnb, and Uber is so remarkable that discussion about them often misses just how hard they are to build. For every successful platform, there are many more that struggle or simply don’t make it. Apple and Google, two of the world’s most valuable companies, have had their share of platform failures as we’ll show. Studying these successes and failures, we’ve identified half a dozen key reasons platforms fail, all of which boil down to managers’ misunderstanding of how platforms operate and compete.

Platform businesses bring together producers and users in efficient exchanges of value – Uber, for example, connects drivers and passengers just as YouTube connects videographers and viewers. And, they leverage network effects – the more participants on the platform, the greater the value produced. Managerial mistakes that inhibit value exchange or network effects can kill a platform. Let’s look at the key errors.

1.Failure to optimize “openness”

Because platforms depend on the value created by participants, it’s critical to carefully manage the platform’s “openness” – the degree of access that consumers, producers, and others have to a platform, and what they’re allowed to do there. If platforms are too closed, keeping potentially desirable participants out, network effects stall; if they’re too open there can be other value-destroying effects, such as poor quality contributions or misbehavior of some participants that causes others to defect.

Steve Jobs failed miserably at managing openness at Apple in the 1980s. He charged developers for toolkits – inhibiting the very software producers he should have wanted on Apple’s platform. The result was that Apple struggled to create a robust platform connecting Apple customers and software producers. For years Apple’s market penetration hung in the single digits. Apple has since figured out this balance, of course, by opening the iOS platforms to app developers. By contrast, Bill Gates opened Windows to both software and hardware developers, making Windows the dominant desktop platform by virtue of its superior ability to connect software and hardware producers with consumers.

Yet platforms can become too open. They must retain enough control over core assets to maintain control of the ecosystem and to make money. Google learned this lesson when Amazon and Samsung fragmented (“forked” in tech lingo) the open Android platform to create their own open-source versions. Google Android quickly lost market share to the new versions. Reacting quickly, Google regained control of the Android system by restricting access to difficult-to-replicate services such as mapping and by shifting important application programming interfaces (APIs) to the proprietary Google Play Store. Android’s story demonstrates that platform openness is one of the key managerial decisions that can determine platform success or failure.

2. Failure to engage developers

Opening platforms the right amount is necessary but not sufficient. The platform owner must also show software developers what’s in it for them if they contribute. In 2013, Johnson Controls invited developers to help them build Panoptix, an energy efficiency platform for buildings and office space. But by early 2015 they stopped accepting new submissions to their open market and discontinued their API support for external developers. Panoptix had not attracted enough new apps to justify pouring resources into supporting this limited external development.

It’s not enough to open the door and set the table. Successful platforms engage in platform evangelism, providing developers with resources to innovate, feedback on design and performance, and rewards for participation. Think of it this way: To host a successful event you must plan carefully, invite the right people, have the right food, and manage competition with the party next door. If Android throws a Hawaiian luau with a five-course feast, free travel, and attendees get to meet Robert Downey Jr. and Sandra Bullock the same night that Johnson Controls offers crackers in Cleveland and asks attendees to cover their own costs, which party will developers attend?

3. Failure to share the surplus

Having valuable interactions is the reason to participate on a platform. The consumer, the producer, and the platform all win if the division of value works for everyone. But if one party gets insufficient value, then they have no reason to participate. Back in 2000, several automakers including Daimler-Chrysler, Ford, GM, Nissan and others invested in Covisint, an online marketplace intended to match buyers and suppliers of auto parts. Unfortunately, Covisint’s ownership structure and auction format heavily favored auto companies (the consumers on the platform) while forcing suppliers into fierce price competition, leaving them with little or no residual value. As a result, parts suppliers left the platform and the market never became sustainably profitable. In 2004, the residual assets were sold off for a mere $7 million, a tiny fraction of the $500 million auto manufacturers had invested.

A simple rule for platform managers is to take less value than you make, and share value fairly with all participants.

4. Failure to launch the right side

Platform managers have to carefully determine which side of the platform market to emphasize, and when. Sometimes at launch it’s important to focus on attracting consumers over producers, sometimes it’s the reverse, and sometime both sides need equal attention from the outset.

Despite huge fanfare and an experienced platform leader, Google Health failed. Google Health was intended to be the premier place for consumers to consolidate their health information. Google tried its preferred strategy of focusing first on the consumer side of the market, an approach that worked beautifully for search, email, and maps. But this time, Google needed to focus first on providers — the other side of the market. Consumers might have used the service if the doctors and insurers who held their information were willing to engage. But they didn’t welcome the scrutiny or the loss of control over data they already possessed. Securing their participation will be critical if health-information platforms are to succeed.

5. Failure to put critical mass ahead of money

Do you remember Billpoint? It was the digital payment system eBay pushed before it gave up and acquired PayPal. As the insider on an established platform, Billpoint should have won. But where Billpoint emphasized fraud prevention, PayPal emphasized ease of use. While Billpoint charged higher transaction fees, PayPal gave away $5 and $10 payments to users who signed up other users. Fraud prevention can keep platform costs down over the long term but puts friction on user transactions, which dissuades value-creating activity. PayPal ate the costs of fraud and emphasized rapid growth by simplifying transactions and incenting participants to attract others. As a result, PayPal rapidly surpassed Billpoint as the payment system of choice on eBay. Conceding defeat in 2002, eBay bought PayPal for $1.4 billion and phased out Billpoint a year later. Billpoint made the mistake of emphasizing revenue generation at the start rather than, first, attracting a critical mass of participants.

Even after the subsidies end, platform monetization that comes at the expense of building network effects is rarely sustainable in the long run as it works against the core mechanism by which platforms create value at scale.

6. Failure of imagination

Perhaps the most egregious platform failure is to simply not see the platform play at all. It is also one of the hardest for traditional firms to avoid. Firms guilty of this oversight never get past the idea that they sell products when they could be building ecosystems. Sony, Hewlett Packard (HP), and Garmin all made the mistake of emphasizing products over platforms. Before the iPhone launched in 2007, HP dominated the handheld calculator space for science and finance. Yet today, consumers can purchase near perfect calculator apps on iTunes or on Google Play and at a fraction of the cost of a physical calculator. Apple and Google did not create these emulators; they merely enabled them by providing the platform that connects app producers and consumers who need calculators.

Sony has sold some of the best electronic products ever made: It once dominated the personal portable music space with the Walkman. It had the world’s first and best compact disc players. By 2011, its PlayStation had become the best-selling game console of all time. Yet, for all its technological prowess Sony focused too much on products and not enough on creating platforms. (What became of Sony’s players? A platform – iOS – ate them for lunch.) Garmin, as a tailored mapping device, suffered a similar fate. As of 2012, Garmin had sold 100 million units after 23 years in the market. By contrast, iPhone sold 700 million units after just eight years in the market. More people get directions from an iPhone than from a Garmin, not only because of Apple maps but also because of Google Maps and Waze. As platforms, iOS and Android have ecosystems of producers, consumers, and others that have helped them triumph over such products as the Cisco Flip camera, the Sony PSP, the Flickr photo service, the Olympus voice recorder, the Microsoft Zune, the Magnus flashlight, and the Fitbit fitness tracker.

When a platform enters the market, product managers who focus on features are not just measuring the wrong things, they’re thinking the wrong thoughts.

TWEETABLE TAKEAWAYS

]]>http://platformed.info/platform-failure-why-the-mighty-fail/feed/0http://platformed.info/platform-failure-why-the-mighty-fail/Will Microsoft help LinkedIn go enterprise?http://feedproxy.google.com/~r/platformed/~3/3X356uSAQww/
http://platformed.info/will-microsoft-help-linkedin-go-enterprise/#respondTue, 14 Jun 2016 13:47:37 +0000http://platformed.info/?p=5483Sangeet’s note: LinkedIn just got acquired by Microsoft. Over the last several years, LinkedIn has been tentatively trying to move into the enterprise CRM space on the strength of its extensive data. In this guest post, Myk Pono, an entrepreneur, marketing and product growth consultant, analyses LinkedIn’s strengths in enterprise vs. Salesforce’s play in that space. Towards the end, I lay out two possible scenarios that will either grow or weaken LinkedIn’s enterprise platform stack. Over to Myk.

TLDR: Linkedin owns the most accurate professional data on over 400M professionals, but it lacks tools and infrastructure to unlock real value from that massive pool of raw data.

Understanding LinkedIn vs. Salesforce

Salesforce has infrastructure and functionality; Linkedin has data
The Salesforce CRM is still the company’s core product despite their diversified product line marketing cloud, data solution, customer support and success. The CRM acts as a hub to connect to other products.

Salesforce CRM provides deep functionality while taking significant resources to get companies started. However, upon implementing Salesforce for your organization, you’re beginning with a clean sheet as no customer data is available to you. Salesforce tried to solve this problem with the Data.com acquisition. However, Data.com’s lead data is not high on freshness and accuracy.

Salesforce has data accuracy issues
The success of lead nurturing, account based sales, and marketing all depend on accurate lead data and tracking. Salesforce has had its own share of data accuracy issues. Salesforce gets this. Many products built on top of Salesforce were built to solve the problems of lead duplication, data accuracy, and enrichment.

Linkedin has what Salesforce is desperately missing – accurate and fresh data.

The Platform Stack, developed by Sangeet Paul Choudary, helps us visualize how Linkedin and Salesforce differ. Linkedin has a tremendous advantage in the network/community layer, which enables it to build a sizeable personal data on its users. Still, Linkedin finds itself without the infrastructure or more specifically tools to use this data to capture Salesforce customers.

LinkedIn as an open API play

Salesforce has tools, and Linkedin has data. It is far easier for one to build tools than for the other to acquire data. If Linkedin makes its API more open and accessible to third-party developers, it will boost SaaS companies in the sales enablement market to build on top of its platform. Linkedin will be able to instantly charge a percentage of revenue generated by the products using its API. Companies that rely heavily on build Chrome extensions to export Linkedin data will be at a disadvantage if they don’t move to the platform. Linkedin can take a cut of these transactions.

LinkedIn will do more than bring in a new source of revenue when moving to a platform business model by expanding the infrastructure layer. It will also encourage many companies in the sales ecosystem to move away from Salesforce.

Outbound email solutions, such as Outreach.io, Sendbloom, Yesware, Toutapp, Replyapp, make up an active niche in the sales enablement marketplace. Access to Linkedin’s data layer would provide these companies and others like them with the opportunity to reach larger markets and integrate contact data into their existing solutions. Linkedin can ask for a percentage of revenues and learn data on open rates to enhance their user profiles.

Sangeet’s Note:

I agree with Myk’s overall point about data being the more difficult asset to replicate. That is central to the idea of the platform stack. Accordingly, building out the infrastructure layer to move into CRM makes a lot of sense. However, with the Microsoft acquisition, there are two varied scenarios that might play out.

1. Weakening of the network and data layers: Microsoft, that has never quite understood the network and data layers, mismanages the acquisition and kills the two layers that already work well for LinkedIn.

2. Rise of the infrastructure layer: Microsoft, with its deep prowess of building developer ecosystems, lets LinkedIn continue to independently manage the network and data layers and augments that with its ability to foster a developer ecosystem to build the infrastructure layer.

It will be interesting to watch and see how this plays out.

]]>http://platformed.info/will-microsoft-help-linkedin-go-enterprise/feed/0http://platformed.info/will-microsoft-help-linkedin-go-enterprise/Blockchain and the new face of decentralizationhttp://feedproxy.google.com/~r/platformed/~3/IrhYXED3IRo/
http://platformed.info/blockchain-and-the-new-face-of-decentralization/#respondThu, 09 Jun 2016 05:50:47 +0000http://platformed.info/?p=5475This post was co-authored with Griffin Anderson, founder of Blockchain as a Platform.

Decentralization is a key theme in the shift from pipes to platforms. Pipe businesses relied on a centralized model of value creation and exchange. The model was built around a supply chain that they one or managed through contracts. Platforms decentralized the value creation and exchange.

Today’s platforms, Uber, Airbnb, Etsy, and others, all have one thing in common, they are scaled intermediaries that operate a decentralized model of value creation and exchange. Their exchange is considered decentralized because both the supply and demand side are directly controlled by the platform operator. For example, Uber operates a decentralized transportation exchange. The exchange was once controlled by the taxi industry, through the issuance of licenses and capital expenditure requirements. These prerequisites limited the number of taxi drivers available in a given city and thus limited supply side. By limiting supply side, the taxi industry controlled the exchange of rides in a given city, making it very difficult for anyone to become a taxi driver. Uber decentralized the supply side, by allowing any driver the opportunity to drive and serve travelers.

Despite the fact that Uber’s exchange is decentralized, Uber still exercises significant control over the platform. This is because Uber owns the identity of its participants, the transportation logistics, the payment mechanisms, the pricing, and the rules that govern the marketplace. More importantly, Uber – as a central intermediary – manages both the openness of the platform to its participants and the governance of their participation. As an intermediary, Uber poses all the threats that traditional intermediaries have posed while managing and regulating markets.

This is why the blockchain could create a whole new model of platform intermediation.

The blockchain has many definitions but there are two key aspects that make it of particular interest for the future of governance. First, it leverages a peer-to-peer network to govern transactions and interactions across a distributed community. Second, it manages this governance through a decentralized ledger that benefits from having a distributed computing infrastructure and a common protocol making it nearly impossible to create a fraudulent transaction.

Intermediaries and the risks they carry

Historically, intermediaries such as banks, financial institutions, governments, policy makers, and corporations filled the role of the trusted advisor. They operated a set of protocols that provided a layer of trust, on which all commerce could operate. Intermediaries were a necessary outcome of moving from a local market economy to an industrial economy run by capital. While intermediaries worked to increase trust and reliability in the functioning of markets, history is filled with disasters where the intermediary injected doubt and mistrust into the system. One such disaster was the 08’ financial crisis.

As platforms transform the economy, we’re seeing massive consolidation in markets where platforms benefit from winner-take-all. Not all markets show these characteristics but we’ve seen several platforms benefit from this at national and global scales over the last decade. As these platforms scale their role as intermediaries, they often extend their function in ways that may harm the ecosystem that relies on them. Last fall, we saw Uber increase its commission from 20% to 25% hurting the income of black cab drivers Forbes. Without debating the merits of the change, the move did reveal the hidden risks of relying on platform intermediaries.

Blockchain-based models of governance

Blockchain startups all over the world are trying to address this risk. The blockchain provides the ability to codify any piece of software and deploy it on top of itself. This includes the ability to codify all the roles and functions that an intermediary has historically performed. The code is then deployed across many distributed computers and with a high level of certainty, we can assume the code will execute in the same way every time. This unique architecture makes the blockchain very suitable to create an alternate model of platform governance. Today’s blockchain startups take the foundational building blocks required to build a platform and decentralize them. Building blocks such as identity, governance, banking, credit, data, and payments are being re-imagined and codified on the blockchain. These are early days but distributed technologies like the blockchain could signal a shift towards decentralized intermediaries.

TWEETABLE TAKEAWAYS

How the blockchain will change governance of today’s systems Share this

The transformative power of the blockchain lies in decentralization of governance Share this

]]>http://platformed.info/blockchain-and-the-new-face-of-decentralization/feed/0http://platformed.info/blockchain-and-the-new-face-of-decentralization/The rise of full-stack solutionshttp://feedproxy.google.com/~r/platformed/~3/14YUiZTitic/
http://platformed.info/the-rise-of-full-stack-solutions/#respondSun, 24 Apr 2016 15:05:58 +0000http://platformed.info/?p=5470In the course of my work advising business leaders on the ongoing platform revolution, I enjoy the privilege of getting a ringside view of key shifts in business as they start showing up across industries. One of those shifts that I’ve begun to observe over the course of my recent discussions is the rise in importance of, what I’ve begun to call, the full-stack solution.

THE FULL-STACK SOLUTION
The term full-stack is often misused and misrepresented but I’m using this term in the specific context of the Platform Stack that I lay out in my book Platform Scale and in the blog post here.

Traditionally, pipe businesses built products and services and sold them to customers. Increasingly, businesses are starting to think like platforms even though they may not claim to be but;ding platforms and may not even look like technology-enabled businesses.

The Full-Stack Solution creates an end-to-end solution for the user across all layers of the platform stack. There are several characteristics that these solutions have.

The full-stack solution consists of multiple products and services.

This is not merely a portfolio of products, they are also integrated with each other at the data layer so that the consumer experience is preserved across the different products and services.

The products/services are rarely all owned by a single company. In most cases, an ecosystem of partner companies come together to power the full-stack solution.

The composition of the full-stack solution is determined by user need, not by product/service availability.

Value to the consumer is not delivered through usage of the product or service alone. In addition to product/service value (infrastructure layer), value may also be offered on the basis of data captured (personalisation or analytics) and through a community of use (network layer) that builds up around the products/services.

Traditional pharmacies sell medicines. They are in the business of selling medicines, not in the business of improving patient health. Increasingly, pharmacies are recognising an opportunity for creating a full-stack solution to address the problem of patient health. Medicines are only one part of the solution. Pharmacies are using patient purchase data to create a detailed profile of the patient and attract other wellness providers to co-create a full-stack health solution for the patient based on their unique data profile.

Consumer electronics manufacturers have been moving in this direction by bundling connected services that enhance the usage of their physical products. In a similar vein, FMCG companies have been creating interactive services to complement product usage. For example, a company selling skincare products may launch a suite of skincare management (digital) services and create communities of usage around the product, while also leveraging the usage data to personalise skincare recommendations for the consumer.

THINKING FULL-STACK

The fundamental mindset shift while providing a full-stack solution is to stop thinking in terms of the products and services you own today, or even in terms of the ones that you can create tomorrow, and start thinking in terms of the full stack of products and services required to guarantee user outcomes. Inevitably, this requires an ecosystem of participants to come together. It is unlikely for one company to own all the products and services required to solve a user need comprehensively and guarantee the final outcome.

The creation of full-stack solutions will also be heavily dependant on data-driven feedback from consumers. As consumers choose different products and services and use them in combination, the solution provider will better understand the unique combinations of products and services that work best and the gaps that exist in provisioning a comprehensive solution.

Finally, while co-creatiing a comprehensive solution has its benefits, it lends itself to additional complexities of governance when multiple partners come together to power an overall solution. Some partners may create more value while others may explicitly capture more value. The balance of incentives by the central coordinating firm will determine how successful such solutions end up being.

There are two broad business models: pipes and platforms. You could be running your startup the wrong way if you’re building a platform, but using pipe strategies.

More on that soon, but first a few definitions.

Pipes

Pipes have been around us for as long as we’ve had industry. They’ve been the dominant model of business. Firms create stuff, push them out and sell them to customers. Value is produced upstream and consumed downstream. There is a linear flow, much like water flowing through a pipe.3

We see pipes everywhere. Every consumer good that we use essentially comes to us via a pipe. All of manufacturing runs on a pipe model. Television and Radio are pipes spewing out content at us. Our education system is a pipe where teachers push out their ‘knowledge’ to children. Prior to the internet, much of the services industry ran on the pipe model as well.

This model was brought over to the internet as well. Blogs run on a pipe model. An ecommerce store like Zappos works as a pipe as well. Single-user SAAS runs on pipe model where the software is created by the business and delivered on a pay-as-you-use model to the consumer.

Platforms

Had the internet not come up, we would never have seen the emergence of platform business models. Unlike pipes, platforms do not just create and push stuff out. They allow users to create and consume value.9 At the technology layer, external developers can extend platform functionality using APIs. At the business layer, users (producers) can create value on the platform for other users (consumers) to consume. This is a massive shift from any form of business we have ever known in our industrial hangover.

TV Channels work on a Pipe model but YouTube works on a Platform model. Encyclopaedia Britannica worked on a Pipe model but Wikipedia has flipped it and built value on a Platform model. Our classrooms still work on a Pipe model but Udemy and Skillshare are turning on the Platform model for education.

Business Model Failure

So why is the distinction important?

Platforms are a fundamentally different business model. If you go about building a platform the way you would build a pipe, you are probably setting yourself up for failure.3

We’ve been building pipes for the last few centuries and we often tend to bring over that execution model to building platforms. The media industry is struggling to come to terms with the fact that the model has shifted. Traditional retail, a pipe, is being disrupted by the rise of marketplaces and in-store technology, which work on the platform model.

Pipe Thinking vs. Platform Thinking

So how do you avoid this as an entrepreneur?

Here’s a quick summary of the ways that these two models of building businesses are different from each other.

User acquisition

User acquisition is fairly straightforward for pipes. You get users in and convert them to transact. Much like driving footfalls into a retail store and converting them, online stores also focus on getting users in and converting them.

Many platforms launch and follow pipe-tactics like the above. Getting users in, and trying to convert them to certain actions. However, platforms often have no value when the first few users come in. They suffer from a chicken and egg problem, which I talk extensively about on this blog. Users (as producers) typically produce value for other users (consumers). Producers upload photos on Flickr and product listings on eBay, which consumers consume. Hence, without producers there is no value for consumers and without consumers, there is no value for producers.

Product Design and Management

Creating a pipe is very different from creating a platform.

Creating a pipe requires us to build with the consumer in mind. An online travel agent like Kayak.com is a pipe that allows users to consume air lie tickets. All features are built with a view to enable consumers to find and consume airline tickets.

In contrast, a platform requires us to build with both producers and consumers in mind. Building YouTube, Dribbble or AirBnB requires us to build tools for producers (e.g. video hosting on YouTube) as well as for consumers (e.g. video viewing, voting etc.). Keeping two separate lenses helps us build out the right features.

The use cases for pipes are usually well established. The use cases for platforms, sometimes, emerge through usage. E.g. Twitter developed many use cases over time. It started off as something which allowed you to express yourself within the constraints of 140 characters (hardly useful?), moved to a platform for sharing and consuming news and content and ultimately created an entirely new model for consuming trending topics. Users often take platforms in surprisingly new directions. There’s only so much that customer development helps your with.

Platform Thinking: Our users interact with each other, using software we create. Our product has no value unless users use it. Tweet

Monetization

Monetization for a pipe, again, is straightforward. You calculate all the costs of running a unit through a pipe all the way to the end consumer and you ensure that Price = Cost + Desired Margin. This is an over-simplification of the intricate art of pricing, but it captures the fact that the customer is typically the one consuming value created by the business.

On a platform business, monetization isn’t quite as straightforward. When producers and consumers transact (e.g. AirBnB, SitterCity, Etsy), one or both sides pays the platform a transaction cut. When producers create content to engage consumers (YouTube), the platform may monetize consumer attention (through advertising). In some cases, platforms may license API usage.

Platform economics isn’t quite as straightforward either. At least one side is usually subsidized to participate on the platform. Producers may even be incentivized to participate. For pipes, a simple formula helps understand monetization:

Customer Acquisition Cost (CAC) < Life TIme Value (LTV)

This formula works extremely well for ecommerce shops or subscription plays. On platforms, more of a systems view is needed to balance out subsidies and prices, and determine the traction needed on either side for the business model to work.

Pipe Thinking: We charge consumers for value we create.

Platform Thinking: We’ve got to figure who creates value and who we charge for that. Tweet

But… Platform Thinking applies to all internet businesses

If the internet hadn’t happened, we would still be in a world dominated by pipes. The internet, being a participatory network, is a platform itself and allows any business, building on top of it, to leverage these platform properties.

Every business on the internet has some Platform properties.

I did mention earlier that blogs, ecommerce stores and single-user SAAS work on pipe models. However, by virtue of the fact that they are internet-enabled, even they have elements that make them platform-like. Blogs allow comments and discussions. The main interaction involves the blogger pushing content to the reader, but secondary interactions (like comments) lend a blog some of the characteristics of platforms. Readers co-create value.

Ecommerce sites have reviews created by users, again an ‘intelligent’ platform model.

The end of pipes

In the future, every company will be a tech company.4 We already see this change around us as companies move to restructure their business models in a way that uses data to create value.

We are moving from linear to networked business models, from dumb pipes to intelligent platforms. All businesses will need to move to this new model at some point, or risk being disrupted by platforms that do.

Tweetable Takeaways

There are two types of business models: Pipes and Platforms. Startups that don’t realize this fail. Tweet

Startups with the best technology often fail because they build for the wrong business model. Tweet

Note: A variation of this article appeared as an op-ed on The Wall Street Journal’s MarketWatch. This was co-authored with Geoffrey Parker (@g2parker, Tulane Univ.) and Marshall Van Alstyne (@infoecon, Boston Univ.). They currently serve as research scientists at the MIT Sloan School of Management.

Nokia just sold to Microsoft. Blackberry announced that it was considering putting itself up for sale. Google’s Android, meanwhile, grows stronger and is moving beyond smartphones to power cars, home electronics, and wearable accessories. Twitter’s heading for a strong IPO with the world’s strongest platform for influence and dissemination. While Barnes&Noble is parting company with the Nook and struggling to survive, a thriving Amazon and Kindle continue to transform publishing, most recently with the launch of a fan fiction platform. In the hotel industry, Airbnb poses a serious threat to the revenues of established players and is disrupting the housing market.

Platform Disruption

We used to live in a world where commerce flowed linearly. Firms added value to products, shipped them out and sold them to consumers. Producers and consumers held very distinct roles. Value was created upstream and flowed downstream.

Now, market upstarts are displacing market leaders faster than ever before as entire industries transform. We are in the midst of a seismic shift in business models, powered by the Internet and a generation of connected users.

Business leaders, today, develop platforms that connect diverse participants with one another and enable them to interact and transact. On the Internet, anyone can be a producer. Today’s network platforms aid the creation of entirely new markets by connecting producers and consumers with each other.

Three forces are powering the rise of platforms: ubiquitous network access with ever-increasing mobile penetration, reputation systems that enable trust among distributed strangers, and access to low cost shared infrastructure with tools and data to capture and coordinate interactions.

Three factors driving disruption

We predict three factors will drive this disruption:

Platforms will displace high cost gatekeepers with meritocratic crowds.2 YouTube and eBay flip the gatekeeping process used in media and retail. In lieu of professional editors and buyers, anyone can produce and the market itself decides what the market wants.

Platforms will unlock new value from spare resources and user-generated content.1 Airbnb hosts and RelayRides’ cars are the spare rooms and idle rides of thousands of individuals. Much of Facebook’s appeal is the newsfeed produced from constant user activity. Instagram’s $1 billion sale was a consequence of the work, not of 13 employees, but of more than 30 million contributors.

The new rules of a platformed world

Ultimately, this transformation redefines competition. Firms that once sought advantage based on the strength of their internal resources and channel access now face competitors that harness armies of connected users and ecosystems of resources. Apple’s App Store, hosting nearly a million applications, offers a compelling testimony to the power of ecosystems. More buyers on eBay attract more sellers, which in turn attracts more buyers. More freelancers on Upwork attract more job postings and vice versa. Such feedback loops enable these businesses to grow into massive juggernauts. Businesses win based on their ability to captivate third parties and connect them to each other through creative interactions.

The rise of ecosystems also means that old linear rules no longer work given new platform realities. In operations, just-in-time inventory gets trumped by just-not-mine inventory. The IT function transforms from client server support to cloud service solution. In marketing, the profit maximizing price is often at or below zero. Charging every user can destroy network effects, yet data and network effects create critical competitive advantage.

Platforms aren’t merely a Silicon Valley obsession. Walmart continues to invest in big data and is leading a retail evolution to the store-as-platform model. Nike+ is showing how the shoe can become a connected platform. Car manufacturers are building connected cars. And GE is forging ahead with its smart grid platform.

Threats to Platform Innovation

But, for every GE moving forward, there is an incumbent resisting change, often relying on regulators to stave off emerging platforms. Uber’s disruption of public transportation has had to contend with many regulatory hurdles. Airbnb has run afoul of housing laws. And Kickstarter crowdfunding has been caught by public securities laws. Since regulation often lags innovation, this can succeed for a time.

So what should you do to thrive in a Platformed world?

Will you be the disrupter or the disrupted? To act on platform opportunities, consider the three factors transforming industry and embrace them:

Remake the role that experts play inside your business to leverage user capabilities outside your business. Build social curation and reputation systems to employ the collective intelligence and judgment of your users.

Connect consumers to their best product options, regardless of source, through data-driven matchmaking. The firm that builds an OpenTable for consumer finance, considering appetites for risk and reputations of products that deliver on promises, would help buyers make sense of the dizzying array of complex and disconnected products. The value would be enormous.

Finally, solve a consumer problem in your industry by marshaling spare resources. If you’re in transportation, build systems that employ other people’s trucks before expanding your own fleet.

Platform opportunities are all around us. Industries like Education, HealthCare, Insurance, and Legal Services, are ripe for disruption. In an increasingly connected future, platforms will only grow in importance. We need to construct the frameworks and rules to allow everyone a fair shot at success in this new world.

In 2011, Nokia’s CEO Stephen Elop sent out the “Burning Platform” manifesto to his employees. It was too late; the rules had already changed. What happened to Nokia and Blackberry can happen to any business that doesn’t leverage the power of platforms. But, for those willing to open their ecosystems and aid their consumers, the future looks bright indeed.

]]>http://platformed.info/the-platform-revolution-why-now-and-what-next/feed/0http://platformed.info/the-platform-revolution-why-now-and-what-next/The future of competitionhttp://feedproxy.google.com/~r/platformed/~3/Afh67atawzU/
http://platformed.info/the-future-of-competition/#respondWed, 24 Feb 2016 12:47:23 +0000http://platformed.info/?p=5392Understanding competitive strategy has long been an obsession of CEOs and business leaders. A lot of the drive for understanding the nature of competition stems from the assumption that business is a zero-sum game. Till very recently, that seemed true. Today, it doesn’t.

Michael Porter’s work on competitive strategy (not least the five forces model) has long served as some form of cornerstone for business strategy. The idea was that business success relied on the creation of moats and management of these five forces. The goal of business, in the Porterian sense, was to beat the competition.

But over the last fifteen years, we’ve seen a significant shift in how we think about competitive strategy. This started first with Blue Ocean Strategy dispelling the idea that zero-sum competition was all that one must obsess over. In parallel, Christensen’s work on disruptive innovation gained further ground as firms realised that your future competitor may look nothing like your current competitors.

Several things changed over the last couple of decades. First, the internet and global connectivity ensured that expansion of markets was no longer as onerous as it used to be. Second, with the rapid pace of innovation over the last two decades, innovation has rapidly become much more important than winning zero-sum competitive games.

But most importantly, the internet allows entirely new markets to be created that didn’t exist in the past. Two aspects of this were explored by Chris Andersen when he looked at how the internet leads to the creation of long tail demand (and supply) leading to market interactions that would never have existed in the past (Book: The Long Tail) and how the internet allowed the creation of markets where products and services could be exchanged for free (Book: Free).

How platforms change competition

While both long tail interactions and free interactions have changed how we think about strategy, the most transformative shift to impact competition yet may only just be starting out. This is the ability to create entirely new markets and bring order to existing disordered markets. This is what platforms do.

The notion of competition changes dramatically with platforms.

First, traditional competition was built on exclusive access to supply-side resources e.g. an oil field. Platform competition, instead, is built on exclusive access to the ecosystem around the platform and the data about their interactions. The platforms with the most active ecosystems and the ability to mine their interaction data win.

Second, while traditional competition played zero-sum games, platforms focus on growing the pie with others in their industry participating on them. Collaboration co-exists with competition. Today, Ford doesn’t simply have to worry about competing with Apple or Google, it has to also figure out how to participate in Apple’s ecosystem in some way so as not to be left behind like Nokia and Blackberry. Strategic considerations on recognising competition and their key source of competitive advantage aren’t straightforward anymore. We’ve seen this with how Android has had to repeatedly stave off competition from members of its own ecosystem, like Samsung and Amazon.

I’m writing about competition because my research partners – Marshall Van Alstyne and Geoffrey Parker – and I have been digging into this a lot of late and have worked on advising several industry leaders on the competitive movements that they see in their industry. We’ve put together a lot of our observations in our forthcoming book Platform Revolution. We’ve also written an article in the April issue of the Harvard Business Review discussing the intricacies of competition in a world of platforms.

The deck below showcases some of our work in this area in a fast pacy read. If you’d like to get a deeper view, you should get a copy of Platform Revolution and watch out for the next issues of the HBR as well. But for now, have a look at the deck below to whet your appetite on this topic.